1. Field of the Invention
The present invention relates to a measurement method and system for use in conjunction with a humidity or gas concentration sensor.
2. Description of Background Art
U.S. Pat. No. 5,033,284 discloses a calibration method, wherein a correction factor of the sensor reading can be computed by way of transiently deviating the temperature of the humidity or gas concentration sensor. This method is applicable to an automatic self-test of the measurement device at intermittent intervals. In the method, the partial pressure of the gas under measurement is assumed to stay constant during imposed deviation of the sensor temperature.
During normal function of the device, the reading can be updated quite frequently within the confines set by the measurement noise. However, as the self-calibration step takes a relatively long time and excludes simultaneous measurement operation of the device, the self-calibration step can be carried out only infrequently. Hence, if the partial pressure of the gas under measurement does not remain constant during the self-calibration step, an erroneous correction is made on the device reading until the next self-calibration is performed. During the self-calibration step, the measurement noise can be filtered extremely effectively, for example, by way of taking a plurality of measurement values during the temperature change, and then applying the least squares method to fit a linear or polynomial response function with the measurement data.
U.S. Pat. No. 5,792,938 (Gokhfeld) relates to a moisture measurement method using a humidity sensor, wherein the sensor response is measured at two different temperatures, and the measurement value difference or slope of response function is directly used as the output signal of the device.
This method is not problematic with regard to changes in water vapor partial pressure during the measurement cycle. However, in this case, the measurement noise causes a larger error in the output signal as compared with other techniques if the measurements are taken at only two points. Furthermore, the method involves a long update period of output signals even in normal operation, not merely during the self-calibration step, as is the case in U.S. Pat. No. 5,033,284, described above.
Both of the above-describe methods are capable of reducing offset errors that occur in measurement devices due to calibration error or instability.
It is an object of the present invention to provide an entirely novel method capable of overcoming the drawbacks of the above-described prior art techniques.
This and other objects are achieved using a method wherein the temperature of the humidity or gas concentration sensor is changed cyclically, and the response to the temperature change is measured in the sensor output signal. Herein, the temperature cycle has a certain specific fundamental frequency xcfx89s. During temperature cycling, sensor response to temperature change is measured (typically from its capacitance or resistance); that is, sensor response (as its capacitance or resistance change) is measured repeatedly as a function of the temperature change. Next, a sensor output signal or a variable (such as relative humidity) computed from the output. signal is subjected to a frequency spectrum analysis, and frequency components different from the fundamental frequency of the temperature cycling sequence are filtered away. A typical humidity sensor has an almost constant capacitance irrespective of the temperature if the relative humidity (RH) is constant. With constant partial pressure of the water vapor, however, the RH varies during the temperature cycling as:
RH=Pw/Pws(T)xc2x7100%,
where Pw=water vapor pressure and Pws(T)=water vapor saturation pressure.
The basic concept of the present invention is to keep the fundamental frequency of the temperature cycling sequence so low that the humidity sensor can stabilize during changes. In other words, the sensor frequency response is adapted to extend beyond the fundamental frequency of the temperature cycling sequence.
If temperature cycling is performed at a frequency whose fundamental component substantially exceeds the frequency response of the sensor (which may be difficult to arrange with concurrent sensors), temperature cycling only affects the sensor""s temperature dependence.
The frequency dependence of the sensor response can be detected from the phase shift with regard to the sensor heating signal. If the sensor has a fast response, there is no additional phase shift. If the sensor has a slow response or if the cycling sequence has a higher fundamental frequency, the phase lag in the sensor output signal becomes larger. When the fundamental frequency of the temperature cycling sequence is equal to the cutoff frequency of the sensor""s frequency response, the phase lag becomes equal to 45xc2x0. Simultaneously, the sensor output signal level begins to fall. In principle, the phase lag can be utilized to compute the response of an ideally fast sensor. Hence, it may be contemplated that this effect could indicate the point at which the sensor due to, e.g., soiling has become so slow as to need servicing.
The result of the frequency spectrum analysis is a basic measurement device response signal from which the sensor output signal is processed and which indicates the measured gas concentration or humidity.
The frequency analysis can be performed electronically utilizing analog techniques, e.g., employing bandpass filters, or digitally through a Fourier transform analysis, e.g., by way of an FFT algorithm.
The method may also be used for self-calibration, whereby the result of the cycling sequence is utilized to compute a corrected measurement device output signal.
The method and system according to the invention offer significant benefits.
Using the method of the present invention, it is possible to take continuous measurements without separate calibration steps, achieving more accurate and stable measurement results than those obtained by prior art methods. Furthermore, the invention can be employed to obtain additional sensor readings in order to improve long-term stability. The temperature sensitivity of the sensor may be monitored in realtime, and corrections can be made if temperature sensitivity changes from its default value.